MLops Engineer
Core
Build and operate the machine learning infrastructure powering speech, audio, and conversational AI teams, ensuring models are trained on high-quality data and deployed with low latency.
Role type
Senior MLOps Engineer (Audio/Speech)
Builds
Scalable GPU-accelerated training infrastructure and low-latency inference pipelines for audio and speech models
Domain
Audio/Speech AI, Cloud Infrastructure, HPC
Deliverable
production ML models
Required skills
Python, PyTorch/TensorFlow/JAX, distributed GPU training, HPC/Slurm cluster management, CI/CD, data pipeline engineering, model optimization
Preferred skills
Self-supervised learning, Apple silicon optimization, mixed-precision training, model monitoring and drift detection, large-scale audio data processing
Technologies
Slurm, HPC clusters, Apple silicon, CI/CD tools
Responsibilities
Design and operate large-scale data pipelines for audio/speech datasets; build distributed GPU training workflows on HPC clusters; optimize model inference for low latency; maintain automated ML lifecycle pipelines; resolve bottlenecks in ML workflows
Seniority
Senior, hands-on IC
